Question

Explain the three (3) location theories.

- Retail Gravity Theory

- Saturation Theory

- Buying Power Index

Answer 1

Retail Gravity Theory

The first theory retailers use in selecting new markets is gravitation theory. The gravitation theory might sound like it is rooted in the principles of Sir Isaac Newton, and that assumption wouldn't be far from the truth! William Reilly coined the idea, which is why it's sometimes called Reilly's law of retail gravitation. It basically states that there is a mathematical equation for figuring out how consumers gravitate toward (in other words, are attracted to) shopping areas. This information can help retailers capture consumers who, for example, live mid-way between two cities. If one city is small, but the other is larger, according to this theory the consumer is more likely to travel to the bigger city even if it is slightly farther away because they perceive it to have better shopping opportunities.

Reilly's theory was later revised to figure out the exact boundary point at which consumers are indifferent to shopping in either location. This breaking point is called the 'point of indifference.'

Gravitation theory assumes two things: that both cities are accessible from main roads and that consumers will look at the population numbers of each city to help make their decision about where to shop. A city with 200,000 people, then, would be more attractive than a city of 100,000 because there are more varied types of stores.

However, this assumption becomes a problem when the perception that a larger city has better shopping opportunities doesn't wind up being true. And since the theory measures distance and difficulty of access in miles and not the amount of time involved, a consumer who goes to the bigger city might find themselves traveling to a mall in heavy downtown traffic as opposed to a shopping complex located right off the interstate, and thus might not make the same choice again.

Saturation Theory

Saturation has attained widespread acceptance as a methodological principle in qualitative research. It is commonly taken to indicate that, on the basis of the data that have been collected or analyzed hitherto, further data collection and/or analysis are unnecessary. However, there appears to be uncertainty as to how saturation should be conceptualized, and inconsistencies in its use. Saturation should be operationalized in a way that is consistent with the research question(s), and the theoretical position and analytic framework adopted, but also that there should be some limit to its scope, so as not to risk saturation losing its coherence and potency if its conceptualization and uses are stretched too widely.

Introduction

Saturation is used in qualitative research as a criterion for discontinuing data collection and/or analysis. Its origins lie in grounded theory (Glaser and Strauss 1967), but in one form or another it now commands acceptance across a range of approaches to qualitative research. Indeed, Saturation is often proposed as an essential methodological element within such work. Failure to reach saturation has an impact on the quality of the research conducted notes that saturation is the most frequently touted guarantee of qualitative rigor offered by authors, Having become the gold standard by which purposive sample sizes are determined in health science research.  

However, despite having apparently attained something of the status of orthodoxy, saturation is defined within the literature in varying ways—or is sometimes undefined—and raises a number of problematic conceptual and methodological issues. Drawing on a number of examples in the literature, some of these issues in relation to three core questions:

1. What? in what way(s) is saturation defined?
2. Where and why? in what types of qualitative research, and for what purpose, should saturation be sought?
3. When and how? at what stage in the research is saturation sought, and how can we assess if it has been achieved?

What? in what way(s) is saturation defined?

The first of these, rooted in traditional grounded theory, uses the development of categories and the emerging theory in the analysis process as the criterion for additional data collection, driven by the notion of theoretical sampling; using a term in common use, but with a more specific definitional focus, this model could thus be Labeled as theoretical saturation. The second model takes a similar approach, but saturation focuses on the identification of new codes or themes, and is based on the number of such codes or themes rather than the completeness of existing theoretical categories. This can be termed inductive thematic saturation. In this model, saturation appears confined to the level of analysis; its implication for data collection is at best implicit. In the third model, a reversal of the preceding logic is suggested, whereby data is collected so as to exemplify theory, at the level of lower-order codes or themes, rather than to develop or refine theory. This model can be termed a priori thematic saturation, as it points to the idea of pre-determined theoretical categories and leads us away from the inductive logic characteristic of grounded theory. Finally, the fourth model—which, again aligning with the term already in common use, we will refer to as data saturation—sees saturation as a matter of identifying redundancy in the data, with no necessary reference to the theory linked to these data; saturation appears to be distinct from formal data analysis.

Table 1

Models of saturation and their principal foci in the research process

Model	Description	Principal focus
Theoretical saturation	Relates to the development of theoretical categories; related to grounded theory methodology	Sampling
Inductive thematic saturation	Relates to the emergence of new codes or themes	Analysis
A priori thematic saturation	Relates to the degree to which identified codes or themes are exemplified in the data	Sampling
Data saturation	Relates to the degree to which new data repeat what was expressed in previous data	Data collection

Where and why? in what types of qualitative research, and for what purpose, should saturation be sought?

Considering the various types of research in which saturation might feature helps to clarify the purposes it is intended to fulfill. When used in a deductive approach to analysis, saturation serves to demonstrate the extent to which the data instantiate previously determined conceptual categories, whereas in more inductive approaches, and grounded theory in particular, it says something about the adequacy of sampling in relation to theory development (although we have seen that there are differing accounts of how specifically this should be achieved). In narrative research, a role for saturation is harder to discern. Rather than the sufficient development of theory, it might be seen to indicate the ‘completeness’ of a biographical account. However, one could question whether the point at which a participant’s story is interpreted as being ‘complete’—having presumably conveyed everything seen to be relevant to the focus of the study—is, in fact, usefully described by the concept of saturation, given the distance that this moves us away from the operationalization of saturation in broadly thematic approaches. This might, furthermore, lead us to ask whether there is the risk of saturation losing its coherence and utility if its potential conceptualization and uses are stretched too widely.

When and how? at what stage in the research is saturation sought, and how can we assess if it has been achieved?

However, interpretations at this stage regarding what might constitute a theme, before even beginning to consider whether identified themes are saturated, will be superficial at best. Moreover, conclusions reached at this stage may not be particularly informative as regards subsequent theory development—pieces of data that appear to be very similar when first considered may be found to exemplify different theoretical constructs on detailed analysis, and correspondingly, data that are empirically dissimilar may turn out to have much in common theoretically. Judgments at this stage will also relate to a framework of themes and categories that is theoretically immature, and that may be subject to considerable modification; for example, the changes that may occur during the successive stages of open, selective and theoretical coding in grounded theory.

Buying Power Index

An index comprised of weighted measures of disposable income, sales data and market factors for a specific region. The index is used by manufacturers and distributors to determine the revenue potential of a particular region.

When athletes are making the transition from successful high school standout to college star to potential pro prospect, there's no shortage of analysts and pundits who weigh in on the potential of the talent to be a big success at the next level. But, athletics aren't the only place where this type of assessment takes place. Retailers go through a similar process to determine whether a market has the potential to be successful in a new location or not. It happens in the form of a calculation known as the Buying Power Index.

The Buying Power Index is a measure that takes into account the buying income, retail sales, and population size of a market to arrive at a score that indicates how successful - or not - a new market might be. Buying income includes measures of personal income (including things such as Social Security payments) and then subtracts taxes. Here's what the equation looks like:

Buying Power Index = 0.5 (the market's percentage of U.S. effective buying income) + 0.3 (the market's percentage of U.S. retail sales) + 0.2 (the market's percentage of U.S. population).

The data for each of those categories comes from the annual ''Survey of Buying Power'' which is published by Sales and Marketing Management. The report includes data based on metropolitan areas, states and regions.

Calculation Example

Let's take a look at an example of a Buying Power Index calculation.

ANC Business Company is trying to decide whether to choose Anytown, USA, or Our City, USA, as a location for its office supply warehouses. ANC's target audience is 35- to 45-year-old small business owners who make more than $60,000 per year. To continue calculating each area's Buying Power Index, we would look up the retail sales, population, and buying income figures in the annual report. We'll create some numbers of our own for this lesson.

To work through the equation, start at the beginning and multiply each number outside the parentheses with the number inside the parentheses, and then add all the number together.

Anytown's BPI might look something like this:

0.5(0.000412)+0.3(0.00081)+ 0.2 (0.00011)=0.000471